DebugIT

In about half a century of antibiotic use, unexpected new challenges have come to light: fast emergence of resistances among pathogens, misuse and overuse of antibiotics; direct and indirect related costs. Antimicrobial resistance results in escalating healthcare costs, increased morbidity and mortality and the emergence or reemergence of potentially untreatable pathogens.

In this context of infectious diseases DebugIT project will (1) detect patient safety issues, (2) learn how to prevent them and (3) actually prevent them in clinical cases. Harmful patterns and trends using clinical and operational information from Clinical Information Systems (CIS) will be detect. This will be done through the 'view' of a virtualised Clinical Data Re-pository (CDR), featuring, transparent access to the original CIS and/or collection and aggregation of data in a local store. Text, image and structured data mining on individual patients as well as on populations will learn us informational and temporal patterns of patient harm.

This knowledge will be fed into a Medical Knowledge Repository and mixed with knowledge coming from external sources (for example guidelines and evidences). After editing and validating, this knowledge will be used by a decision support and monitoring tool in the clinical environment to prevent patient safety issues and report on it.

Outcomes and benefits, both clinical and economical will be measured and reported on. Innovation within this project lays in the virtualisation of Clinical Data Repository through ontology mediation, the advanced mining techniques, the reasoning engine and the consolidation of all these techniques in a comprehensive but open framework. This framework will be implemented, focused on infectious diseases, but will be applicable for all sorts of clinical cases in the future.

For further information, please visit:
http://www.debugit.eu

Project co-ordinator:
Agfa HealthCare (Belgium)

Partners:

  • empirica
  • Gama Sofia Ltd.
  • Institut National de la Santé et de Recherche Medicale
  • Internetový Pristup Ke Zdravotním Informacím Pacienta
  • Linköping University
  • Technological Educational Institute of Lamia
  • University College London
  • University Hospital of Geneva
  • University Medical Center Freiburg
  • University of Geneva

Timetable: from 01/2008 – to 12/2011

Total cost: €8.364.796

EC funding: €6.414.915

Programme Acronym: FP7-ICT

Subprogramme Area: Advanced ICT for risk assessment and patient safety

Contract type: Collaborative project (generic)


Related news article:

Most Popular Now

Free Online Tool Helps Determine Whether…

University of California, Irvine health sciences researchers have created a machine-learning model to predict the probability that a COVID-19 patient will need a ventilator or ICU care. The tool is...

Study Details First Artificial Intellige…

Hospital-based laboratories and doctors at the front line of the COVID-19 pandemic might soon add artificial intelligence to their testing toolkit. A recent study conducted with collaborators from the University...

Accelerating Data Solutions to Save LIVE…

The consortium of COVID-X announces the launch of the ​1st Open Call ​framed in a ​2-year initiative that will invest ​4 million € to fast-track to market 30+ European data...

Significant Disparities in Telemedicine …

After "COVID-19," the term that most people will remember best from 2020 is likely to be "social distancing." While it most commonly applied to social gatherings with family and friends...

Model Used to Evaluate Lockdowns was Fla…

In a recent study, researchers from Imperial College London developed a model to assess the effect of different measures used to curb the spread of the coronavirus. However, the model...

New Virtual Screening Strategy Identifie…

A novel computational drug screening strategy combined with lab experiments suggest that pralatrexate, a chemotherapy medication originally developed to treat lymphoma, could potentially be repurposed to treat COVID-19. Haiping Zhang...

Using Artificial Intelligence to Find Ne…

Scientists have developed a machine-learning method that crunches massive amounts of data to help determine which existing medications could improve outcomes in diseases for which they are not prescribed. The intent...

One in Four Doctors Attacked, Harassed o…

While many physicians benefit from social media by networking with potential collaborators or interfacing with patients, a new study from Northwestern University and the University of Chicago found many physicians...

CliniSys Launches Laboratory Information…

CliniSys has launched a new laboratory information management system for genomic laboratories in the UK. The company has brought GLIMS Genomics to the UK from Europe, where it is being...

The Institute of Healthcare Management C…

The Institute of Healthcare Management has called for honest and open communication about NHS capacity after a snapshot survey revealed the scale of sickness absence across the service. The UK's leading...